Preliminary prediction of individual response to electroconvulsive therapy using whole-brain functional magnetic resonance imaging data.

Electroconvulsive therapy (ECT) works rapidly and has been widely used to treat depressive disorders (DEP). However, identifying biomarkers predictive of response to ECT remains a priority to individually tailor treatment and understand treatment mechanisms. This study used a connectome-based predictive modeling (CPM) approach in 122 patients with DEP to determine if pre-ECT whole-brain functional connectivity (FC) predicts depressive rating changes and remission status after ECT (47 of 122 total subjects or 38.5% of sample), and whether pre-ECT and longitudinal changes (pre/post-ECT) in regional brain network biomarkers are associated with treatment-related changes in depression ratings. Results show the networks with the best predictive performance of ECT response were negative (anti-correlated) FC networks, which predict the post-ECT depression severity (continuous measure) with a 76.23% accuracy for remission prediction. FC networks with the greatest predictive power were concentrated in the prefrontal and temporal cortices and subcortical nuclei, and include the inferior frontal (IFG), superior frontal (SFG), superior temporal (STG), inferior temporal gyri (ITG), basal ganglia (BG), and thalamus (Tha). Several of these brain regions were also identified as nodes in the FC networks that show significant change pre-/post-ECT, but these networks were not related to treatment response. This study design has limitations regarding the longitudinal design and the absence of a control group that limit the causal inference regarding mechanism of post-treatment status. Though predictive biomarkers remained below the threshold of those recommended for potential translation, the analysis methods and results demonstrate the promise and generalizability of biomarkers for advancing personalized treatment strategies

Joint and individual analysis of breast cancer histologic images and genomic covariates

A key challenge in modern data analysis is understanding connections between complex and differing modalities of data. For example, two of the main approaches to the study of breast cancer are histopathology (analyzing visual characteristics of tumors) and genetics. While histopathology is the gold standard for diagnostics and there have been many recent breakthroughs in genetics, there is little overlap between these two fields. We aim to bridge this gap by developing methods based on Angle-based Joint and Individual Variation Explained (AJIVE) to directly explore similarities and differences between these two modalities. Our approach exploits Convolutional Neural Networks (CNNs) as a powerful, automatic method for image feature extraction to address some of the challenges presented by statistical analysis of histopathology image data. CNNs raise issues of interpretability that we address by developing novel methods to explore visual modes of variation captured by statistical algorithms (e.g. PCA or AJIVE) applied to CNN features. Our results provide many interpretable connections and contrasts between histopathology and genetics

HSD3B1 genotype identifies glucocorticoid responsiveness in severe asthma

Asthma resistance to glucocorticoid treatment is a major health problem with unclear etiology. Glucocorticoids inhibit adrenal androgen production. However, androgens have potential benefits in asthma. HSD3B1 encodes for 3β-hydroxysteroid dehydrogenase-1 (3β-HSD1), which catalyzes peripheral conversion from adrenal dehydroepiandrosterone (DHEA) to potent androgens and has a germline missense-encoding polymorphism. The adrenal restrictive HSD3B1(1245A) allele limits conversion, whereas the adrenal permissive HSD3B1(1245C) allele increases DHEA metabolism to potent androgens. In the Severe Asthma Research Program (SARP) III cohort, we determined the association between DHEA-sulfate and percentage predicted forced expiratory volume in 1 s (FEV1PP). HSD3B1(1245) genotypes were assessed, and association between adrenal restrictive and adrenal permissive alleles and FEV1PP in patients with (GC) and without (noGC) daily oral glucocorticoid treatment was determined (n = 318). Validation was performed in a second cohort (SARP I&II; n = 184). DHEA-sulfate is associated with FEV1PP and is suppressed with GC treatment. GC patients homozygous for the adrenal restrictive genotype have lower FEV1PP compared with noGC patients (54.3% vs. 75.1%; P < 0.001). In patients with the homozygous adrenal permissive genotype, there was no FEV1PP difference in GC vs. noGC patients (73.4% vs. 78.9%; P = 0.39). Results were independently confirmed: FEV1PP for homozygous adrenal restrictive genotype in GC vs. noGC is 49.8 vs. 63.4 (P < 0.001), and for homozygous adrenal permissive genotype, it is 66.7 vs. 67.7 (P = 0.92). The adrenal restrictive HSD3B1(1245) genotype is associated with GC resistance. This effect appears to be driven by GC suppression of 3β-HSD1 substrate. Our results suggest opportunities for prediction of GC resistance and pharmacologic intervention

Nonhuman humanitarianism: when ‘AI for good’ can be harmful

Artificial intelligence (AI) applications have been introduced in humanitarian operations in order to help with the significant challenges the sector is facing. This article focuses on chatbots which have been proposed as an efficient method to improve communication with, and accountability to affected communities. Chatbots, together with other humanitarian AI applications such as biometrics, satellite imaging, predictive modelling and data visualisations, are often understood as part of the wider phenomenon of ‘AI for social good’. The article develops a decolonial critique of humanitarianism and critical algorithm studies which focuses on the power asymmetries underpinning both humanitarianism and AI. The article asks whether chatbots, as exemplars of ‘AI for good’, reproduce inequalities in the global context. Drawing on a mixed methods study that includes interviews with seven groups of stakeholders, the analysis observes that humanitarian chatbots do not fulfil claims such as ‘intelligence’. Yet AI applications still have powerful consequences. Apart from the risks associated with misinformation and data safeguarding, chatbots reduce communication to its barest instrumental forms which creates disconnects between affected communities and aid agencies. This disconnect is compounded by the extraction of value from data and experimentation with untested technologies. By reflecting the values of their designers and by asserting Eurocentric values in their programmed interactions, chatbots reproduce the coloniality of power. The article concludes that ‘AI for good’ is an ‘enchantment of technology’ that reworks the colonial legacies of humanitarianism whilst also occluding the power dynamics at play

Detrimental Effects of Environmental Tobacco Smoke in Relation to Asthma Severity

Background: Environmental tobacco smoke (ETS) has adverse effects on the health of asthmatics, however the harmful consequences of ETS in relation to asthma severity are unknown. Methods: In a multicenter study of severe asthma, we assessed the impact of ETS exposure on morbidity, health care utilization and lung functions; and activity of systemic superoxide dismutase (SOD), a potential oxidative target of ETS that is negatively associated with asthma severity. Findings: From 2002-2006, 654 asthmatics (non-severe 366, severe 288) were enrolled, among whom 109 non-severe and 67 severe asthmatics were routinely exposed to ETS as ascertained by history and validated by urine cotinine levels. ETS-exposure was associated with lower quality of life scores; greater rescue inhaler use; lower lung function; greater bronchodilator responsiveness; and greater risk for emergency room visits, hospitalization and intensive care unit admission. ETS-exposure was associated with lower levels of serum SOD activity, particularly in asthmatic women of African heritage. Interpretation: ETS-exposure of asthmatic individuals is associated with worse lung function, higher acuity of exacerbations, more health care utilization, and greater bronchial hyperreactivity. The association of diminished systemic SOD activity to ETS exposure provides for the first time a specific oxidant mechanism by which ETS may adversely affect patients with asthma. © 2011 Comhair et al

Lancet commission on hypertension group position statement on the global improvement of accuracy standards for devices that measure blood pressure

The Lancet Commission on Hypertension identified that a key action to address the worldwide burden of high blood pressure (BP) was to improve the quality of BP measurements by using BP devices that have been validated for accuracy. Currently, there are over 3000 commercially available BP devices, but many do not have published data on accuracy testing according to established scientific standards. This problem is enabled through weak or absent regulations that allow clearance of devices for commercial use without formal validation. In addition, new BP technologies have emerged (e.g. cuffless sensors) for which there is no scientific consensus regarding BP measurement accuracy standards. Altogether, these issues contribute to the widespread availability of clinic and home BP devices with limited or uncertain accuracy, leading to inappropriate hypertension diagnosis, management and drug treatment on a global scale. The most significant problems relating to the accuracy of BP devices can be resolved by the regulatory requirement for mandatory independent validation of BP devices according to the universally-accepted International Organisation for Standardization Standard. This is a primary recommendation for which there is an urgent international need. Other key recommendations are development of validation standards specifically for new BP technologies and online lists of accurate devices that are accessible to consumers and health professionals. Recommendations are aligned with WHO policies on medical devices and universal healthcare. Adherence to recommendations would increase the global availability of accurate BP devices and result in better diagnosis and treatment of hypertension, thus decreasing the worldwide burden from high BP

Meta-analysis of genome-wide association studies of asthma in ethnically diverse North American populations.

Asthma is a common disease with a complex risk architecture including both genetic and environmental factors. We performed a meta-analysis of North American genome-wide association studies of asthma in 5,416 individuals with asthma (cases) including individuals of European American, African American or African Caribbean, and Latino ancestry, with replication in an additional 12,649 individuals from the same ethnic groups. We identified five susceptibility loci. Four were at previously reported loci on 17q21, near IL1RL1, TSLP and IL33, but we report for the first time, to our knowledge, that these loci are associated with asthma risk in three ethnic groups. In addition, we identified a new asthma susceptibility locus at PYHIN1, with the association being specific to individuals of African descent (P = 3.9 × 10(-9)). These results suggest that some asthma susceptibility loci are robust to differences in ancestry when sufficiently large samples sizes are investigated, and that ancestry-specific associations also contribute to the complex genetic architecture of asthma

Asthma Is More Severe in Older Adults

Background: Severe asthma occurs more often in older adult patients. We hypothesized that the greater risk for severe asthma in older individuals is due to aging, and is independent of asthma duration. Methods: This is a cross-sectional study of prospectively collected data from adult participants (N=1130; 454 with severe asthma) enrolled from 2002 – 2011 in the Severe Asthma Research Program. Results: The association between age and the probability of severe asthma, which was performed by applying a Locally Weighted Scatterplot Smoother, revealed an inflection point at age 45 for risk of severe asthma. The probability of severe asthma increased with each year of life until 45 years and thereafter increased at a much slower rate. Asthma duration also increased the probability of severe asthma but had less effect than aging. After adjustment for most comorbidities of aging and for asthma duration using logistic regression, asthmatics older than 45 maintained the greater probability of severe asthma [OR: 2.73 (95 CI: 1.96; 3.81)]. After 45, the age-related risk of severe asthma continued to increase in men, but not in women. Conclusions: Overall, the impact of age and asthma duration on risk for asthma severity in men and women is greatest over times of 18-45 years of age; age has a greater effect than asthma duration on risk of severe asthma

Human subcortical brain asymmetries in 15,847 people worldwide reveal effects of age and sex

The two hemispheres of the human brain differ functionally and structurally. Despite over a century of research, the extent to which brain asymmetry is influenced by sex, handedness, age, and genetic factors is still controversial. Here we present the largest ever analysis of subcortical brain asymmetries, in a harmonized multi-site study using meta-analysis methods. Volumetric asymmetry of seven subcortical structures was assessed in 15,847 MRI scans from 52 datasets worldwide. There were sex differences in the asymmetry of the globus pallidus and putamen. Heritability estimates, derived from 1170 subjects belonging to 71 extended pedigrees, revealed that additive genetic factors influenced the asymmetry of these two structures and that of the hippocampus and thalamus. Handedness had no detectable effect on subcortical asymmetries, even in this unprecedented sample size, but the asymmetry of the putamen varied with age. Genetic drivers of asymmetry in the hippocampus, thalamus and basal ganglia may affect variability in human cognition, including susceptibility to psychiatric disorders